| ---
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| license: apache-2.0
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| authors:
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| - Kunalmod
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| task_categories:
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| - robotics
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| tags:
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| - tsfile
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| - timeseries
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| - tabular
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| modality:
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| - timeseries
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| - tabular
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| pretty_name: SO101 Block-to-Box TsFile
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| configs:
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| - config_name: default
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| data_files:
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| - split: train
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| path: data/kunalmod_so101_groot.tsfile
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| size_categories:
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| - 10K<n<100K
|
| ---
|
|
|
| # SO101 Block-to-Box TsFile
|
|
|
| This dataset provides the numeric robot trajectories from
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| [`Kunalmod/so101_groot`](https://huggingface.co/datasets/Kunalmod/so101_groot) as one Apache TsFile table. The LeRobot
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| v2.1 SO101 demonstrations cover grasping a block and placing it in a box.
|
|
|
| ## Source Dataset
|
|
|
| - Author, repository owner, and uploader: [Kunalmod](https://huggingface.co/Kunalmod) (`Kunalmod`)
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| - License: Apache-2.0
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| - Split: `train`
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| - Scale: 50 episodes, 47,507 frame rows, 1 task, and 50 source Parquet shards
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| - Sampling frequency: 30 fps
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| - Robot type: `so101`
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| - LeRobot codebase version: `v2.1`
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| - Source data layout: `data/chunk-{episode_chunk:03d}/episode_{episode_index:06d}.parquet`
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| - Paper and citation: the source card does not provide either one
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| - Task `0`: `Grasp a block and put it in the box.`
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|
|
| ## Data Layout
|
|
|
| - TsFile: `data/kunalmod_so101_groot.tsfile`
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| - Table: `kunalmod_so101_groot`
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| - Rows: 47,507
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| - Devices: 50, identified by the two TAG columns
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| - Time precision: milliseconds
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| - Per-episode Time range: 0 to 39,600 ms
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|
|
| All 50 episode shards are represented in the table. Filter by `episode_index`
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| and `task_index` to select an episode trajectory.
|
|
|
| ## Schema
|
|
|
| | Column | TsFile type | Role | Meaning |
|
| |---|---|---|---|
|
| | `Time` | TIMESTAMP | TIME | `round(timestamp * 1000)` in milliseconds |
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| | `episode_index` | STRING | TAG | Source episode index stored by the TsFile device/tag mechanism |
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| | `task_index` | STRING | TAG | Source task index stored by the TsFile device/tag mechanism |
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| | `frame_index` | INT64 | FIELD | Frame position within the episode |
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| | `sample_index` | INT64 | FIELD | Source global `index` value |
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| | `action_0` ... `action_5` | FLOAT | FIELD | Six SO101 action components |
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| | `observation_state_0` ... `observation_state_5` | FLOAT | FIELD | Six SO101 joint-state components |
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|
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| The action and state component order is `main_shoulder_pan`,
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| `main_shoulder_lift`, `main_elbow_flex`, `main_wrist_flex`, `main_wrist_roll`,
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| and `main_gripper`.
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|
|
| ## Transform Details
|
|
|
| - `Time` is derived from the source timestamp and restarts at zero for every
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| episode. The source `timestamp` is omitted because it equals `Time / 1000`
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| seconds.
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| - `index` is renamed to `sample_index`; `frame_index` is preserved.
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| - `action[6]` is flattened to `action_0` through `action_5`.
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| - `observation.state[6]` is flattened to `observation_state_0` through
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| `observation_state_5`.
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| - Rows are ordered by `episode_index`, `task_index`, and `Time`.
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| - No source trajectory row, episode, task, action dimension, or state dimension
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| is removed.
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|
|
| ## Videos
|
|
|
| The 100 source MP4 files remain in the original repository and are not
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| included here. Each camera has 50 files at 640x480 and 30 fps:
|
|
|
| - [`observation.images.base`](https://huggingface.co/datasets/Kunalmod/so101_groot/tree/main/videos/chunk-000/observation.images.base)
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| - [`observation.images.wrist`](https://huggingface.co/datasets/Kunalmod/so101_groot/tree/main/videos/chunk-000/observation.images.wrist)
|
|
|
| Their source pattern is
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| `videos/chunk-{episode_chunk:03d}/{video_key}/episode_{episode_index:06d}.mp4`.
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| Use `episode_index` and `frame_index` to align each numeric row with both video
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| streams.
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|
|
| ## Usage
|
|
|
| ```python
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| from tsfile import ColumnCategory, TsFileReader
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|
|
| path = "data/kunalmod_so101_groot.tsfile"
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| reader = TsFileReader(path)
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| table_name = "kunalmod_so101_groot"
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| schema = reader.get_all_table_schemas()[table_name]
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| columns = [
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| column.get_column_name()
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| for column in schema.get_columns()
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| if column.get_category() in (ColumnCategory.TAG, ColumnCategory.FIELD)
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| ]
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|
|
| with reader.query_table(table_name, columns, batch_size=65536) as result:
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| batch = result.read_arrow_batch()
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| print(batch.to_pandas().head())
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| reader.close()
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| ```
|
|
|
| ## Attribution
|
|
|
| The demonstrations were published by [Kunalmod](https://huggingface.co/Kunalmod) under the
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| Apache-2.0 license and were created with
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| [LeRobot](https://github.com/huggingface/lerobot). Cite the original Hugging
|
| Face dataset URL above when using the data.
|
|
|
